Record Details

Fully automated region of interest segmentation pipeline for UAV based RGB images

OAR@ICRISAT

View Archive Info
 
 
Field Value
 
Relation http://oar.icrisat.org/12788/
https://www.sciencedirect.com/science/article/abs/pii/S1537511021002166
https://doi.org/10.1016/j.biosystemseng.2021.08.032
 
Title Fully automated region of interest segmentation pipeline for UAV based RGB images
 
Creator Sadashivan, S
Bhattacherjee, S S
Priyanka, G
Pachamuthu, R
Kholova, J
 
Subject Crop Physiology
 
Description Unmanned Aerial Vehicles (UAVs) have exhibited its potential for efficient and non-invasive crop data acquisition in high throughput crop phenotyping. In general, for analysis of phenotypic traits, there is a need for extracting the region of interest (RoI) from images captured by UAVs. It involves the generation of orthomosaic, which is a complicated and time-intensive process. In this study, a fully automated AI-based pipeline has been proposed for the RoI segmentation from raw RGB images acquired via UAV. The proposed pipeline achieves a near real-time processing speed compared to the other baseline methods. The key feature of the pipeline is the introduction of Sub-Paths, in which the original UAV flight path is divided into several small paths which facilitates parallel processing. The image quality of the extracted RoI has been examined using blind/referenceless image spatial quality evaluator (BRISQUE) and natural image quality evaluator (NIQE). The performance of the proposed pipeline is exemplified with the Leaf Area Index (LAI) estimation on five datasets containing three different crop types and growth stages. Regression analysis has also been performed on the estimated LAI values. Average R2, RMSE, and correlation scores of the estimates are observed to be 0.68, 0.033, and 0.83, respectively.
 
Publisher Elsevier
 
Date 2021-09-24
 
Type Article
PeerReviewed
 
Identifier Sadashivan, S and Bhattacherjee, S S and Priyanka, G and Pachamuthu, R and Kholova, J (2021) Fully automated region of interest segmentation pipeline for UAV based RGB images. Biosystems Engineering, 211. ISSN 1537-5110